Penn Researchers Utilize MRI for Early Diagnosis
of SchizophreniaNew Way of Using MRI May Show Us What the Naked Eye Cannot
See

(Philadelphia, PA) - Researchers may have discovered a new way that may
ultimately assist in the early diagnosis of schizophrenia - by utilizing
MRI to study the patient’s brain. Researchers at the University
of Pennsylvania Health System (UPHS) looked for subtle brain
abnormalities that cannot be seen by the human eye. A study examined the
entire brain, looking at distributed patterns of abnormalities rather
than differences in specific regions of the brain.

“In this study, we used high-dimensional shape transformations
in which we compared a brain image with a template of a normal brain.
Through this comparison, we then determined where and how the patient’s
brain differed from healthy controls,” explained Christos
Davatzikos, PhD, Director of the Section of Biomedical Image
Analysis in the Department of Radiology at Penn. “These methods
are able to identify abnormalities that could not be detected by human
inspection of the images created via MRI And, up until now, structural
MRI has typically been used to diagnose physical anomalies like stroke
or tumors, but it has not been helpful for diagnosis of psychiatric diseases.”

Davatzikos says, “MRI produces images which are traditionally read
mostly by radiologists. Now, we can do a quantitative reading of these
images - bringing out information that is not obvious to the eye; one
can think of computer readings as computational scanners. It’s a
second level that says ‘analyze this image and produce another image
that highlights subtle abnormalities in the brain.’ This is fundamentally
new information now that we can use for a larger spectrum of diseases
and look for early diagnosis and prevention - such as the teen at risk
for developing schizophrenia.”

The results of the study demonstrate that sophisticated computational
analysis methods can find unique structural brain characteristics in schizophrenia
patients, with a predictive accuracy of more than 83%. Recently, Davatzikos
and his group announced that further analysis of this data with even more
sophisticated classification methods achieved a 91% predictive accuracy
for diagnosis of schizophrenia via MRI (MICCAI 2005 meeting, Palm Springs,
CA).

“This is the first time this level of predictive power of MRI for
classification of schizophrenia is demonstrated in a study of this magnitude,”
adds Davatzikos. “This tells us there are unique patterns we can
use and explore when we want to diagnose patients with schizophrenia.
However, the biggest value for this new diagnostic tool will be for early
detection before clinical manifestation of the disease. For this, we will
need to examine teenagers at risk.”

Schizophrenia commonly presents in late adolescence or early adulthood
thereby disrupting normal development and attainment of education and
achieving independence. “If the disease can be detected early, intervention
can ameliorate its potential effects. For example, brain systems implicated
in schizophrenia include those required for learning and memory. Knowing
that these systems have reduced volume in an individual could justify
cognitive remediation efforts that will palliate the deficits and allow
better adaptation,” said Raquel Gur, MD, PhD, Director
of the Schizophrenia Center with the Department of Psychiatry at UPHS,
who performed the studies supported by NIMH.

Davatzikos further explains, “If you can diagnose schizophrenia
early, utilizing MRI along with other tools like genetic disposition,
behavioral profiles and functional imaging -- before a patient actually
develops the disease -- we can try to delay the onset of the disease and
hopefully have a better outcome for the rest of their life.”

“Despite the high accuracy with the MRI classified patients and
healthy controls, the diagnosis of schizophrenia is based on the clinical
presentation,” says Gur. “However, it is time for mental health
professionals to think of neuroimaging as an important diagnostic tool
that merits further research.”

The results of this study are published in the November 2005 issue of
the “JAMA - Archives of General Psychiatry.” You will be able
to access it on-line at: <http://archpsyc.ama-assn.org/> (The article
is titled “Whole-Brain Morphometric Study of Schizophrenia Revealing
a Spatially Complex Set of Focal Abnormalities”).

The name of this study is “Computer-Based Detection of Complex
Patterns of Brain Abnormality in Schizophrenia, Using MRI." NIMH
grants funding supported this study.

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